Naver Mail MCP Server

by Leonamin

Overview Schema Related Servers Score Discussions

Python

Local

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.1.0
Disambiguation5/5
Every tool has a clearly distinct purpose with no ambiguity. Tools are well-organized around specific operations like copying vs. moving mails, different marking states, and separate listing methods. The descriptions clearly differentiate each tool's function.
Naming Consistency5/5
All tools follow a consistent verb_noun naming pattern with clear, descriptive names. The naming convention is uniform throughout (e.g., copy_mails, create_folder, list_mails), making it easy to understand each tool's function at a glance.
Tool Count5/5
With 16 tools, this is well-scoped for a mail management server. Each tool earns its place by covering essential operations like folder management, mail listing, status updates, and basic utilities without being excessive or redundant.
Completeness5/5
The toolset provides complete CRUD/lifecycle coverage for email management. It includes folder operations (create, delete, rename, list), mail operations (list, get detail, copy, move, delete), status management (read/unread, important/unimportant), and utility functions (ping, debug). No obvious gaps exist for the domain.
Average 2.8/5 across 16 of 16 tools scored. Lowest: 1.7/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.
If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.
MCP servers without a LICENSE cannot be installed.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. '메일 삭제' only states the action without revealing critical traits: whether deletion is permanent or reversible, if it requires specific permissions, what happens on success/failure, or any rate limits. This is inadequate for a destructive operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While concise with just two words, this is under-specification rather than effective brevity. The description fails to front-load essential information and doesn't earn its place by adding value beyond the tool name. It lacks structure for a tool with significant implications.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's destructive nature, lack of annotations, and no output schema, the description is severely incomplete. It doesn't address behavioral aspects, error handling, or usage context, leaving the agent with insufficient information to invoke this tool safely and correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'mail_uids' clearly documented as an array of strings for UIDs of mails to delete. The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description '메일 삭제' (delete mails) restates the tool name without adding specificity. It doesn't distinguish this tool from sibling tools like 'delete_folder' or 'move_mails' that also involve deletion operations. While the verb and resource are clear, this is essentially a tautology of the tool name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing mail UIDs from list operations), exclusions (e.g., not for folders), or comparisons to siblings like 'move_mails' for archiving instead of deletion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. '메일 폴더 삭제' implies a destructive mutation, but it doesn't specify critical details: whether deletion is permanent or reversible, if it requires specific permissions, what happens to contained emails, or error conditions. For a destructive tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single phrase ('메일 폴더 삭제'), which is concise and front-loaded with the core action. However, it's overly terse—it could benefit from slightly more detail (e.g., on scope or effects) without losing efficiency. Every word earns its place, but the brevity limits usefulness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (destructive operation with 1 parameter) and lack of annotations or output schema, the description is incomplete. It doesn't explain the outcome (e.g., success/failure response), side effects, or safety considerations. For a deletion tool, this leaves critical gaps for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with 'folder_name' clearly documented as '삭제할 폴더 이름' (folder name to delete). The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description '메일 폴더 삭제' (Delete mail folder) states the verb (delete) and resource (mail folder), providing a basic purpose. However, it doesn't distinguish this tool from sibling tools like 'delete_mails' or 'rename_folder'—it's unclear if this deletes the folder structure versus its contents, or how it differs from other deletion tools. The purpose is clear but lacks sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites (e.g., folder must be empty), exclusions (e.g., cannot delete default folders), or comparisons to siblings like 'delete_mails' or 'rename_folder'. Without any usage context, the agent must infer based on the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'debugging' but doesn't specify whether this is a read-only inspection, a diagnostic test, or a modification tool. It lacks details on permissions, side effects, rate limits, or output format, leaving significant gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient phrase in Korean that conveys the core purpose without unnecessary words. It's appropriately sized for a simple tool, though it could be more front-loaded with specific actions if it were more detailed. There's no wasted text, but it's borderline under-specified rather than concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (implied by 'debugging' which can involve various operations), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns, how it performs debugging, or any behavioral traits. For a tool that might inspect system states, more context is needed to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the absence of inputs. The description doesn't need to add parameter details, and it appropriately doesn't mention any. This meets expectations for a parameterless tool, though it doesn't compensate for any gaps since there are none.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description '환경 변수 및 서버 상태 디버깅' (environment variables and server status debugging) states what the tool does in general terms - debugging. However, it's vague about the specific action (e.g., whether it retrieves, modifies, or tests these values) and doesn't distinguish it from siblings like 'ping' (which might also check server status). It's better than a tautology but lacks specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context, or exclusions, nor does it differentiate from sibling tools like 'ping' (which might test connectivity) or other debugging-related operations. Users must infer usage from the vague purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states it's an inquiry operation, implying it's read-only, but doesn't specify any behavioral traits such as authentication requirements, rate limits, pagination behavior, or what the output looks like. For a tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single phrase ('메일 폴더 목록 조회'), which is very concise and front-loaded with the core purpose. There's no wasted text, making it efficient, though it could benefit from additional context to improve completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimal but incomplete. It lacks details on behavioral aspects like output format or usage context, which are important even for simple tools. Without annotations or output schema, the description should provide more completeness to guide the agent effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and the schema description coverage is 100% (since there are no parameters to describe). The description doesn't need to add parameter semantics, so a baseline score of 4 is appropriate, as it doesn't introduce confusion or redundancy.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description '메일 폴더 목록 조회' (Mail folder list inquiry) states the verb ('조회' - inquiry) and resource ('메일 폴더' - mail folders), providing a basic purpose. However, it doesn't distinguish this from sibling tools like 'list_mails' or 'list_mails_paginated', which also list mail-related items. The purpose is clear but lacks sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose 'list_folders' over other listing tools like 'list_mails', or any prerequisites or context for usage. This leaves the agent with no explicit or implied usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('copy') but doesn't clarify whether this creates duplicates, preserves originals, requires specific permissions, or has side effects like updating timestamps. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with zero wasted words. It front-loads the core action and resource efficiently, making it easy to parse quickly. Every word earns its place by contributing essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's mutation nature (copying mails), lack of annotations, and absence of an output schema, the description is insufficient. It doesn't address behavioral traits, error conditions, or return values, leaving the agent with incomplete context for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with both parameters clearly documented in the schema itself. The description adds no additional semantic context beyond what the schema provides (e.g., format examples, constraints, or relationships between parameters). This meets the baseline for high schema coverage but doesn't enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('copy') and resource ('mails to another folder'), making the purpose immediately understandable. It doesn't explicitly differentiate from the sibling 'move_mails' tool, which would be helpful for disambiguation, but the verb 'copy' is specific enough to convey the core function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'move_mails' or other mail manipulation tools. It lacks context about prerequisites (e.g., needing valid mail UIDs and folder names) or typical use cases, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('create') but does not cover critical aspects like required permissions, whether the operation is idempotent, error conditions, or effects on existing data. This leaves significant gaps for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool is a mutation operation with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits, error handling, or return values, which are essential for an agent to use the tool effectively in context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the parameter 'folder_name' clearly documented. The description does not add any extra semantic meaning beyond what the schema provides, such as naming constraints or examples, so it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description '새 메일 폴더 생성' (Create new mail folder) clearly states the verb ('create') and resource ('mail folder'), making the purpose evident. However, it does not differentiate from sibling tools like 'rename_folder', which also modifies folders, leaving room for improvement in specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It lacks context such as prerequisites (e.g., permissions), exclusions, or comparisons to related tools like 'list_folders' or 'rename_folder', leaving the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. While '조회' implies a read-only operation, the description doesn't specify authentication requirements, rate limits, error conditions, or what constitutes '상세 정보' (detailed information). For a tool with no annotation coverage, this leaves significant behavioral questions unanswered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized for a simple retrieval tool and front-loads the essential information. Every word earns its place in conveying the core function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mail retrieval tool with no annotations and no output schema, the description is insufficient. It doesn't explain what '상세 정보' includes (headers, body, attachments, metadata), doesn't mention authentication requirements, and provides no context about the mail system or data format. With siblings that handle mail operations, more context about this tool's specific role is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the schema already fully documents both parameters (uid and format with enum values). The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain uid format requirements, provide format selection guidance, or clarify the 'text' format limitation mentioned in the schema ('내용은 없음' - no content).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('조회' - retrieve/view) and resource ('특정 메일의 상세 정보' - specific mail's detailed information), making the purpose immediately understandable. However, it doesn't explicitly differentiate this tool from similar siblings like 'list_mails' or 'list_mails_paginated' which might also provide mail information but in list format rather than detailed view.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'list_mails' and 'list_mails_paginated' that also retrieve mail information, there's no indication that this tool is for detailed single-mail retrieval versus list-based retrieval. No prerequisites, exclusions, or comparison context is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the output format options (JSON or text) but lacks details on permissions, rate limits, error handling, or what 'recent' means (e.g., time frame, sorting). This leaves significant gaps for a tool that likely interacts with email data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, stating the core functionality in a single sentence. However, it could be slightly improved by structuring it to highlight key points more clearly, such as separating format implications, but overall it is efficient with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It does not explain the return values, error conditions, or behavioral traits like data freshness or access controls. For a tool with potential complexity in email retrieval, this leaves the agent with insufficient context to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so the schema fully documents the parameters. The description adds minimal value by mentioning the format options but does not provide additional semantic context beyond what the schema already specifies, such as implications of choosing 'text' over 'json'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as retrieving a list of recent emails with a specified count and format. It uses specific verbs ('최근 N개 메일 목록 조회') and identifies the resource ('메일'), but does not explicitly differentiate from sibling tools like 'list_mails_paginated' or 'get_mail_detail', which prevents a score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention sibling tools such as 'list_mails_paginated' for paginated results or 'get_mail_detail' for detailed views, nor does it specify contexts or exclusions for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions pagination support but fails to describe critical behaviors: whether this is a read-only operation, how pagination works (e.g., token-based vs. offset), what the return format includes, error conditions, or rate limits. The description is too minimal for a tool with mutation siblings like delete_mails.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point with no wasted words. It's appropriately sized for a simple retrieval tool, though it could be more front-loaded with key differentiators from siblings.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (pagination logic) and lack of both annotations and output schema, the description is incomplete. It doesn't explain what the tool returns, how pagination tokens work, or error handling. For a paginated query tool among mutation siblings, this leaves significant gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no additional meaning about parameters beyond what's in the schema (e.g., it doesn't explain pagination mechanics or format implications). Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as '페이징을 지원하는 메일 목록 조회' (pagination-supported mail list retrieval), which specifies the verb (retrieve/list), resource (mails), and key capability (pagination). It distinguishes from the sibling 'list_mails' by explicitly mentioning pagination support, though it doesn't fully explain how it differs functionally beyond that.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'list_mails' or 'get_mail_detail'. It mentions pagination support but doesn't specify scenarios where pagination is necessary (e.g., large datasets) or when to prefer non-paginated versions. No prerequisites or exclusions are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the action but doesn't reveal whether this is a reversible operation, if it requires specific permissions, what happens on success/failure, or any side effects. The description is minimal and lacks necessary context for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a simple tool and gets straight to the point without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what '중요 상태' (important status) means in this system, what the tool returns, or error conditions. Given the complexity of modifying mail states, more context is needed for proper agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'mail_uids' well-documented in the schema as '중요 처리할 메일들의 UID 목록' (list of UIDs of mails to mark important). The description adds no additional parameter information beyond what the schema provides, meeting the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('중요 상태로 변경' - change to important status) and resource ('메일' - mails), making the purpose understandable. However, it doesn't distinguish this tool from its sibling 'mark_mails_unimportant' beyond the obvious opposite action, missing explicit differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'mark_mails_unimportant' or 'mark_mails_read/unread'. It doesn't mention prerequisites, context, or exclusions, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While it correctly indicates a state modification (not read-only), it fails to describe important behaviors: whether this is reversible, if it requires specific permissions, what happens with invalid UIDs, whether it's batched or atomic, and what the tool returns (success/failure indicators). The description is minimal and lacks operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single Korean phrase that directly states the tool's function. There's zero wasted language, and the meaning is front-loaded immediately. Every word earns its place by contributing essential information about the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what the tool returns (success status, error handling), doesn't mention side effects or dependencies, and provides no context about the mail system's behavior. The agent would need to guess about important operational aspects despite having a clear but minimal purpose statement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'mail_uids' clearly documented in the schema as '읽음 처리할 메일들의 UID 목록' (list of UIDs of mails to mark as read). The description adds no additional parameter information beyond what the schema already provides, so it meets the baseline for high schema coverage without adding value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('읽음 상태로 변경' - change to read status) and the resource ('메일' - mails), making the purpose immediately understandable. It distinguishes from siblings like 'mark_mails_unread' by specifying the opposite state change. However, it doesn't explicitly mention that this modifies mail metadata rather than content retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites (like needing valid UIDs), when not to use it, or how it differs from similar operations like 'get_mail_detail' (which might mark as read automatically). The existence of 'mark_mails_unread' as a sibling tool creates ambiguity without usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states the state change but doesn't disclose whether this is reversible, if it affects mail visibility/filtering, permission requirements, or side effects. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It is appropriately sized for a simple state-change operation and front-loads the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'unimportant' means operationally, whether the change is persistent, what the response looks like, or error conditions. Given the complexity of modifying mail states and lack of structured data, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'mail_uids' clearly documented in the schema as '중요하지 않음 처리할 메일들의 UID 목록' (list of UIDs of mails to mark unimportant). The description adds no additional parameter context beyond what the schema provides, meeting the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('중요하지 않음 상태로 변경' - change to unimportant status) and resource ('메일' - mails), making the purpose understandable. It distinguishes from siblings like 'mark_mails_important' by specifying the opposite state, but doesn't explicitly contrast with other mail-modification tools like 'mark_mails_read' or 'delete_mails'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, appropriate contexts, or when not to use it (e.g., vs. deleting or archiving mails). It relies solely on the tool name and description for implicit differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('change to unread status') but lacks details on permissions required, whether the change is reversible, side effects (e.g., updating timestamps), error handling, or response format. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Korean that directly states the tool's purpose without unnecessary words. It is front-loaded with the core action, making it easy to parse quickly, and every part of the sentence contributes essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity as a mutation operation with no annotations and no output schema, the description is incomplete. It lacks details on behavioral aspects (e.g., what happens on success/failure), usage context, and return values, leaving gaps that could hinder an AI agent's ability to invoke it correctly without additional assumptions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'mail_uids' clearly documented in the schema as '읽지 않음 처리할 메일들의 UID 목록' (list of UIDs of emails to mark as unread). The description adds no additional meaning beyond this, such as format examples or constraints, so it meets the baseline for high schema coverage without compensating value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('메일을 읽지 않음 상태로 변경' translates to 'Change emails to unread status') and identifies the resource (emails). It distinguishes from siblings like 'mark_mails_read' by specifying the opposite state, though it doesn't explicitly contrast with other tools like 'mark_mails_important' or 'delete_mails' beyond the implied state change.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description does not mention prerequisites (e.g., needing valid mail UIDs), exclusions (e.g., not applicable to already unread mails), or contextual cues (e.g., use for marking emails as unread after accidental reads). It relies solely on the tool name for differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'move' implies mutation, it doesn't specify whether this is reversible, what permissions are required, what happens to the original mails, or error handling. The description lacks critical behavioral context for a mutation operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized and front-loaded with the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after moving (are mails removed from source?), what the response looks like, error conditions, or how this differs from copying. More context is needed for proper tool understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters completely. The description doesn't add any additional meaning about the parameters beyond what's in the schema descriptions, meeting the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('move') and resource ('mails to another folder'), making the purpose immediately understandable. However, it doesn't differentiate from the sibling 'copy_mails' tool, which performs a similar operation with different semantics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives like 'copy_mails' or 'delete_mails'. The description doesn't mention prerequisites, error conditions, or appropriate contexts for moving versus copying mails.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the action (rename) but doesn't mention permissions required, whether the operation is reversible, potential side effects, error conditions, or what happens if the new name conflicts. This is a significant gap for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient phrase that directly states the tool's purpose with zero wasted words. It's appropriately sized and immediately communicates the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the tool returns, error handling, or behavioral constraints. The agent would need to guess about important aspects of using this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both parameters clearly documented in the schema. The description doesn't add any parameter-specific information beyond what's in the schema, so it meets the baseline for high schema coverage without providing extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description '메일 폴더 이름 변경' (Mail folder rename) clearly states the verb (rename/change) and resource (mail folder). It's specific about what the tool does, though it doesn't explicitly differentiate from sibling tools like 'create_folder' or 'delete_folder' beyond the obvious action difference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing folder), exclusions, or comparisons to sibling tools like 'create_folder' or 'delete_folder' that also manipulate folders.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. '서버 상태 확인' implies a read-only diagnostic operation, but it doesn't specify what 'status' means (e.g., connectivity, health metrics, uptime), whether authentication is required, potential rate limits, or what the output format might be. For a tool with zero annotation coverage, this leaves significant behavioral questions unanswered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient phrase ('서버 상태 확인') that communicates the core purpose with zero wasted words. It's appropriately sized for a simple diagnostic tool and is front-loaded with the essential information. Every element of the description earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally complete. It states what the tool does but lacks behavioral context and usage guidance. For a diagnostic tool that likely returns status information, the absence of output schema means the description should ideally hint at return values, but the basic purpose statement is adequate for the simplest use cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage (empty schema). The description doesn't need to compensate for any parameter documentation gaps. The baseline for zero parameters with complete schema coverage is 4, as there are no parameters whose semantics need explanation beyond what the structured schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description '서버 상태 확인' (server status check) clearly states what the tool does with a specific verb ('확인' - check) and resource ('서버 상태' - server status). It distinguishes from all sibling tools which are mail/folder management operations, making the purpose unambiguous. It doesn't specify the exact mechanism (e.g., ping response time, health endpoint) but provides adequate clarity for a simple diagnostic tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There are no explicit instructions about when this tool is appropriate, what prerequisites might exist, or what context warrants its use. The agent must infer usage from the purpose alone, which is insufficient for optimal tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![NaverMail-MCP-Server MCP server](https://glama.ai/mcp/servers/Leonamin/NaverMail-MCP-Server/badges/card.svg)](https://glama.ai/mcp/servers/Leonamin/NaverMail-MCP-Server)

Score Badge

Copy to your README.md:

[![NaverMail-MCP-Server MCP server](https://glama.ai/mcp/servers/Leonamin/NaverMail-MCP-Server/badges/score.svg)](https://glama.ai/mcp/servers/Leonamin/NaverMail-MCP-Server)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Leonamin/NaverMail-MCP-Server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server